Labeling problems may be solved to support a variety of different functionality. Labels, for instance, may be assigned to nodes to describe characteristics of the node. The labels may be used to describe the characteristics of the node that involve the node itself, characteristics of the node in relation to another node, and so on.
Labeling problems may employ beliefs that may be used to assist in solving the labeling problem. For example, beliefs may be formed for nodes that describe a particular characteristic of the node that is to be labeled and therefore a belief for the node may pertain to a label that is to be assigned to the node. These beliefs may also be shared between nodes to assist in solving a label for other nodes. In this way, nodes may leverage knowledge passed to the node from other nodes to solve a labeling problem for the node. However, in some instances passing of these beliefs between nodes may actually hinder accuracy in solving the labeling problem for the node. Thus, conventional techniques may be forced to unlearn this knowledge in order to arrive at a correct label for a node, which may cause an increase in resource usage and therefore cause these conventional techniques to be ill suited for certain applications, such as applications that involve user interaction.